Skip to main content
Share Your Experience: Take the 2024 Developer Survey

Questions tagged [feature-selection]

Methods and principles of selecting a subset of attributes for use in further modelling

Filter by
Sorted by
Tagged with
4 votes
2 answers
3k views

What features from sound waves to use for an AI song composer?

I am planning on making an AI song composer that would take in a bunch of songs of one instrument, extract musical notes (like ABCDEFG) and certain features from the sound wave, preform machine ...
user3377126's user avatar
1 vote
0 answers
48 views

Trying to come up with a feature to improve emotion classifier based on facial movement using facial landmarks

I managed to create an emotion recognition system that uses dense optical flow on each entire frame. While the accuracy range is within 80-90% with cross-validation, I am aiming to improve the ...
user3377126's user avatar
10 votes
7 answers
3k views

Data science projects explained step by step?

I am looking for a website or book where several practical examples are given step by step, explaining how they choose the relevant features, the model selection procedure, etc...
cpumar's user avatar
  • 807
1 vote
0 answers
88 views

How to include class as a feature

I am currently experimenting with the idea of including the class of a feature vector as a separate feature. My work is about preposition selection in learner language use. I want to train a ...
lennyklb's user avatar
  • 374
2 votes
1 answer
529 views

How to select features from text data?

I have a data set of questions belonging to ten different categories namely (definitions, factoids, abbreviations, fill in the blanks, verbs, numerals, dates, puzzle, etymology and category relation). ...
untitledprogrammer's user avatar
5 votes
3 answers
905 views

Is automatic feature detection feasible?

I am searching for pointers to algorithms for feature detection. EDIT: all the answers helped me a lot, I cannot decide which one I should accept. THX guys! What I did: For discrete variables (i.e....
Fabian Werner's user avatar
4 votes
3 answers
1k views

How to find the input variables for a classification problem?

I am working on a classification problem. I have 1000+ features in this dataset. I don't know how to select the right variables/ features that can actually contribute to predicting the output. What ...
Arun's user avatar
  • 717
1 vote
1 answer
166 views

design pattern for extracting features

I am looking for a design pattern that is relevant to a module that extracts features. I want to define a certain number of features over my data points, and then according to the performance and the ...
mic's user avatar
  • 513
1 vote
1 answer
239 views

Does high error rate in regression imply the data set is unpredictable?

I have a data set of video watching records in a 3G network. In this data set, 2 different kind of features are included: user-side information, e.g., age, gender, data plan and etc; Video watching ...
ice_lin's user avatar
  • 157
1 vote
1 answer
33 views

Shifting dataPoints up by a constant (Is there an issue with too many 0's for features?)

I am currently collecting second by second data regarding buyer vs seller initiated trades for different financial instruments (securities mostly). If there are more buyer initiated trades in a given ...
user3256725's user avatar
2 votes
1 answer
60 views

Does a NB wrapper consider feature subset size?

while comparing two different algorithms to feature selection I stumbled upon the follwing question: For a given dataset with a discrete class variable we want to train a naive bayes classifier. We ...
deemel's user avatar
  • 151
5 votes
2 answers
1k views

Time series prediction

I am trying to predict a time serie from another one. My approach is based on a moving windows. I predict the output value of the serie from the following features: the previous value and the 6 past ...
Lucas Morin's user avatar
  • 2,244
1 vote
2 answers
187 views

Time series: variations as a feature

I am trying to predict clients comportement from market rates. The value of the products depends on the actual rate but this is not enough. The comportement of the client also depends on their ...
Lucas Morin's user avatar
  • 2,244
3 votes
1 answer
2k views

Machine Learning for hedging/ portfolio optimization?

With increasingly sophisticated methods that work on large scale datasets, financial applications are obvious. I am aware of machine learning being employed on financial services to detect fraud and ...
Nitesh's user avatar
  • 1,615
8 votes
1 answer
2k views

Document classification: tf-idf prior to or after feature filtering?

I have a document classification project where I am getting site content and then assigning one of numerous labels to the website according to content. I found out that tf-idf could be very useful ...
user991710's user avatar
2 votes
1 answer
142 views

scikit-learn OMP mem error

I tried to use OMP algorithm available in scikit-learn. My net datasize which includes both target signal and dictionary ~ 1G. However when I ran the code, it exited with mem-error. The machine has ...
sshanks's user avatar
  • 21
63 votes
10 answers
67k views

Machine learning - features engineering from date/time data

What are the common/best practices to handle time data for machine learning application? For example, if in data set there is a column with timestamp of event, such as "2014-05-05", how you can ...
Igor Bobriakov's user avatar
13 votes
2 answers
4k views

What features are generally used from Parse trees in classification process in NLP?

I am exploring different types of parse tree structures. The two widely known parse tree structures are a) Constituency based parse tree and b) Dependency based parse tree structures. I am able to ...
working's user avatar
  • 231
26 votes
2 answers
18k views

Text categorization: combining different kind of features

The problem I am tackling is categorizing short texts into multiple classes. My current approach is to use tf-idf weighted term frequencies and learn a simple linear classifier (logistic regression). ...
elmille's user avatar
  • 361
4 votes
1 answer
1k views

Understanding output stepAIC

I am using the stepAIC function in R to do a bi-directional (forward and backward) stepwise regression. I do not understand what each return value from the function ...
universalkernel's user avatar
60 votes
8 answers
128k views

Does scikit-learn have a forward selection/stepwise regression algorithm?

I am working on a problem with too many features and training my models takes way too long. I implemented a forward selection algorithm to choose features. However, I was wondering does scikit-learn ...
Maksud's user avatar
  • 725
22 votes
2 answers
7k views

How to choose the features for a neural network?

I know that there is no a clear answer for this question, but let's suppose that I have a huge neural network, with a lot of data and I want to add a new feature in input. The "best" way ...
marcodena's user avatar
  • 1,667
6 votes
1 answer
3k views

How to normalize results of Singular Value Decomposition (SVD) between 0 and 1?

I'm building a recommender system and using SVD as one of the preprocessing techniques. However, I want to normalize all my preprocessed data between 0 and 1 because all of my similarity measures (...
covfefe's user avatar
  • 293
11 votes
4 answers
4k views

Feature Extraction Technique - Summarizing a Sequence of Data

I often am building a model (classification or regression) where I have some predictor variables that are sequences and I have been trying to find technique recommendations for summarizing them in the ...
B_Miner's user avatar
  • 702
16 votes
4 answers
2k views

What are the implications for training a Tree Ensemble with highly biased datasets?

I have a highly biased binary dataset - I have 1000x more examples of the negative class than the positive class. I would like to train a Tree Ensemble (like Extra Random Trees or a Random Forest) on ...
gallamine's user avatar
  • 418
9 votes
1 answer
261 views

Learning signal encoding

I have a large number of samples which represent Manchester encoded bit streams as audio signals. The frequency at which they are encoded is the primary frequency component when it is high, and there ...
ragingSloth's user avatar
  • 1,824
8 votes
3 answers
169 views

Feature selection for tracking user activity within an application

I am developing a system that is intended to capture the "context" of user activity within an application; it is a framework that web applications can use to tag user activity based on requests made ...
Joshua Barron's user avatar
15 votes
4 answers
6k views

How to specify important attributes?

Assume a set of loosely structured data (e.g. Web tables/Linked Open Data), composed of many data sources. There is no common schema followed by the data and each source can use synonym attributes to ...
vefthym's user avatar
  • 503
70 votes
11 answers
40k views

What is dimensionality reduction? What is the difference between feature selection and extraction?

From wikipedia: dimensionality reduction or dimension reduction is the process of reducing the number of random variables under consideration, and can be divided into feature selection and feature ...
alvas's user avatar
  • 2,410

1
16 17 18 19
20